This section endeavors to supply a context or background for the various exemplary embodiments of the invention as recited in the claims. The content herein may comprise subject matter that could be utilized, but not necessarily matter that has been previously utilized, described or considered. Unless indicated otherwise, the content described herein is not considered prior art, and should not be considered as admitted prior art by inclusion in this section.
The study and analysis of online social networks has become more prominent with the increased availability and decreased cost of online access and communication. Generally, a social network may be considered a social structure comprised of individuals, groups of individuals and/or organizations (collectively referred to herein as “entities”) represented as “nodes” that are connected to one another by one or more types of relationships or interdependencies (e.g., friends, kin, knowledge, employment, hobbies, interests). Online social networks and structures, such as Facebook®, have become valuable tools not only for personal communication purposes but also for informational, entertainment and advertising functions, for example.
With increased usage of online social networks, participants are also more vulnerable to appropriation of personal data and private information. It is difficult to provide access to data from social networks (e.g., family information, medical histories, networks of devices associated with the users, networks of sensors used to collect data, such as video cameras) while maintaining the privacy and anonymity of individuals associated with nodes in the networks. As an example, it is possible to analyze social networks, such as Facebook®, in order to obtain data concerning the users and participants, such as health risks based on analyses of the individual's “friends” within the social network, for example. Moreover, it is recognized that social network data and related analyses can provide a wealth of latent information concerning an individual's tastes, health and likely behavior. Because of the predictive power and informative nature, data from social networks is at once both valuable and extremely sensitive. Therefore, privacy should be maintained whenever this data is collected, analyzed or otherwise utilized.